{"id":"https://openalex.org/W4309302775","doi":"https://doi.org/10.1145/3539597.3570465","title":"Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs","display_name":"Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs","publication_year":2023,"publication_date":"2023-02-22","ids":{"openalex":"https://openalex.org/W4309302775","doi":"https://doi.org/10.1145/3539597.3570465"},"language":"en","primary_location":{"id":"doi:10.1145/3539597.3570465","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539597.3570465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2211.08568","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007704896","display_name":"Linhao Luo","orcid":"https://orcid.org/0000-0003-0027-942X"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Linhao Luo","raw_affiliation_strings":["Monash University, Melbourne, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0003-0027-942X","affiliations":[{"raw_affiliation_string":"Monash University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081525024","display_name":"Gholamreza Haffari","orcid":"https://orcid.org/0000-0001-7326-8380"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Gholamreza Haffari","raw_affiliation_strings":["Monash University, Melbourne, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0001-7326-8380","affiliations":[{"raw_affiliation_string":"Monash University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008056593","display_name":"Shirui Pan","orcid":"https://orcid.org/0000-0003-0794-527X"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shirui Pan","raw_affiliation_strings":["Griffith University, Brisbane, QLD, Australia"],"raw_orcid":"https://orcid.org/0000-0003-0794-527X","affiliations":[{"raw_affiliation_string":"Griffith University, Brisbane, QLD, Australia","institution_ids":["https://openalex.org/I11701301"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"778","last_page":"786"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.988099992275238,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9853000044822693,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6955188512802124},{"id":"https://openalex.org/keywords/ode","display_name":"Ode","score":0.6346507668495178},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.5912999510765076},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5592672228813171},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5232038497924805},{"id":"https://openalex.org/keywords/link","display_name":"Link (geometry)","score":0.48607924580574036},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.44534531235694885},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4427153170108795},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4376704692840576},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38944903016090393},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33878859877586365},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1833488941192627}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6955188512802124},{"id":"https://openalex.org/C34862557","wikidata":"https://www.wikidata.org/wiki/Q178985","display_name":"Ode","level":2,"score":0.6346507668495178},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.5912999510765076},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5592672228813171},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5232038497924805},{"id":"https://openalex.org/C2778753846","wikidata":"https://www.wikidata.org/wiki/Q6554239","display_name":"Link (geometry)","level":2,"score":0.48607924580574036},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.44534531235694885},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4427153170108795},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4376704692840576},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38944903016090393},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33878859877586365},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1833488941192627},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3539597.3570465","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539597.3570465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2211.08568","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2211.08568","pdf_url":"https://arxiv.org/pdf/2211.08568","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/424767","is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/424767","pdf_url":null,"source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference output"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2211.08568","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2211.08568","pdf_url":"https://arxiv.org/pdf/2211.08568","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W569478347","https://openalex.org/W1924770834","https://openalex.org/W1981276685","https://openalex.org/W2021910005","https://openalex.org/W2029792996","https://openalex.org/W2167467982","https://openalex.org/W2562676961","https://openalex.org/W2735478962","https://openalex.org/W2788789723","https://openalex.org/W2808492412","https://openalex.org/W2963557251","https://openalex.org/W2963755523","https://openalex.org/W2964015378","https://openalex.org/W2965683718","https://openalex.org/W2970479204","https://openalex.org/W2971278153","https://openalex.org/W2998116985","https://openalex.org/W2998313947","https://openalex.org/W3007404067","https://openalex.org/W3091393595","https://openalex.org/W3101251439","https://openalex.org/W3101588560","https://openalex.org/W3101999497","https://openalex.org/W3109841242","https://openalex.org/W3122137342","https://openalex.org/W3129664826","https://openalex.org/W3133518153","https://openalex.org/W3153189161","https://openalex.org/W3153939186","https://openalex.org/W3161012769","https://openalex.org/W3166605255","https://openalex.org/W3175992967","https://openalex.org/W3197994189","https://openalex.org/W3211666987","https://openalex.org/W4213091601","https://openalex.org/W4220779330","https://openalex.org/W4285070053","https://openalex.org/W4287601676","https://openalex.org/W4287755062","https://openalex.org/W4288072954","https://openalex.org/W4289763970","https://openalex.org/W4293387938","https://openalex.org/W4298324034","https://openalex.org/W4308609499","https://openalex.org/W4308829019","https://openalex.org/W4318828927","https://openalex.org/W4320463723","https://openalex.org/W6600292188","https://openalex.org/W6600339963"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4378510483","https://openalex.org/W4221142204"],"abstract_inverted_index":{"Link":[0],"prediction":[1,103],"on":[2,15,74,104,164],"dynamic":[3,16,62,105,166],"graphs":[4,106],"is":[5,33,45,139],"an":[6],"important":[7],"task":[8],"in":[9,37,49],"graph":[10,17,50,167],"mining.":[11],"Existing":[12],"approaches":[13],"based":[14,73],"neural":[18,76,92,95,183],"networks":[19],"(DGNNs)":[20],"typically":[21],"require":[22],"a":[23,46,70,108,114],"significant":[24],"amount":[25],"of":[26,90,132,177],"historical":[27],"data":[28],"(interactions":[29],"over":[30,42,116],"time),":[31],"which":[32,44],"not":[34],"always":[35],"available":[36],"practice.":[38],"The":[39],"missing":[40],"links":[41],"time,":[43],"common":[47],"phenomenon":[48],"data,":[51],"further":[52],"aggravates":[53],"the":[54,75,88,91,101,120,123,135,154,175],"issue":[55],"and":[56,61,94,156,180],"thus":[57],"creates":[58],"extremely":[59],"sparse":[60,136],"graphs.":[63],"To":[64],"address":[65],"this":[66],"problem,":[67],"we":[68],"propose":[69],"novel":[71],"method":[72],"process,":[77],"called":[78],"Graph":[79],"Sequential":[80],"Neural":[81],"ODE":[82],"Process":[83],"(GSNOP).":[84],"Specifically,":[85],"GSNOP":[86,118,138,171],"combines":[87],"advantage":[89],"process":[93,184],"ordinary":[96],"differential":[97],"equation":[98],"that":[99,145,170],"models":[100],"link":[102,160],"as":[107],"dynamic-changing":[109],"stochastic":[110],"process.":[111],"By":[112],"defining":[113],"distribution":[115],"functions,":[117],"introduces":[119],"uncertainty":[121],"into":[122],"predictions,":[124],"making":[125],"it":[126],"generalize":[127],"to":[128,134,142,152],"more":[129],"situations":[130],"instead":[131],"overfitting":[133],"data.":[137],"also":[140],"agnostic":[141],"model":[143],"structures":[144],"can":[146,172],"be":[147],"integrated":[148],"with":[149],"any":[150],"DGNN":[151],"consider":[153],"chronological":[155],"geometrical":[157],"information":[158],"for":[159],"prediction.":[161],"Extensive":[162],"experiments":[163],"three":[165],"datasets":[168],"show":[169],"significantly":[173],"improve":[174],"performance":[176],"existing":[178],"DGNNs":[179],"outperform":[181],"other":[182],"variants.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2022-11-25T00:00:00"}
